Automated seamline construction for high-quality high-resolution orthomosaics

ABSTRACT

A system for semi-automated feature extraction comprising an image analysis server that receives and initializes a plurality of raster images, a feature extraction server that identifies and extracts image features, a mosaic server that assembles mosaics from multiple images, and a rendering engine that provides visual representations of images for review by a human user, and a method for generating a cost raster utilizing the system of the invention.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No.14/789,877 titled “AUTOMATED SEAMLINE CONSTRUCTION FOR HIGH-QUALITYHIGH-RESOLUTION ORTHOMOSAICS”, filed on Jul. 1, 2015, which claims thebenefit of, and priority to, U.S. provisional patent application Ser.No. 62/019,876, titled “METHODS FOR CREATING A COST RASTER FOR AUTOMATEDAND SEMI-AUTOMATED FEATURE EXTRACTION” and filed on Jul. 1, 2014, theentire specifications of each of which are incorporated herein byreference.

BACKGROUND OF THE INVENTION Field of the Art

This disclosure relates to the field of image processing, and isparticularly concerned with the automatic construction of high-qualityhigh-resolution orthomosaics from satellite or aerial imagery.

Discussion of the State of the Art

To build an orthomosaic from satellite or aerial imagery, participatingimages are first orthorectified, co-registered, and tonally balanced,and then a seamline vector is constructed for every pair (in essence) ofimages A and B that overlap. Once all these seamlines are computed,images are clipped by their seamlines to form mosaic regions that fittogether like puzzle pieces. In high-quality orthomosaics, the seamlinesare as inconspicuous as possible so that the mosaic actually appearsseamless (seamlines are inconspicuous when local mosaic content showsnatural transition going from one side of the seamline to the other.) Inthe past, to get this level of quality required manual construction ofthe seamlines—a tedious and labor-intensive process. Automated systemsfor constructing orthomosaics must generate seamlines automatically and,if required, necessitate only minimal human touch-up. An existingapproach for doing this is to auto-generate a “cost” raster perseamline, and automatically extract the seamline as a least cost pathbetween two points using, say, Dijkstra's algorithm. What has beenmissing is a recipe for creating a cost raster that leads to aninconspicuous seamline (inconspicuous over a diverse range of imagecontent) and especially in the most complex areas where there is humandevelopment. Prior art cost rasters for seamline construction were basedprimarily on tonal similarity between corresponding pixels in theinvolved images—this is insufficient in many cases to yield aninconspicuous seamline.

What is needed is a way of constructing a cost raster that will lead toan inconspicuous seamline, over a diverse range of image content,especially in the most complex areas where there is human development.This is especially needed for high-quality, high-resolution, RGBorthomosaics that may be formed from any part of the globe.

SUMMARY OF THE INVENTION

Accordingly, the inventor has conceived and reduced to practice, in apreferred embodiment of the invention, a system and method for automatedconstruction of inconspicuous seamlines in an orthomosaic, the seamlinesrealized as least cost paths extracted from respective cost rasters. Themain novel aspect of the invention is the design of the cost rasteritself, which yields inconspicuous seamlines over a diverse range ofimage content, especially in the most complex areas where there is humandevelopment.

According to a preferred embodiment of the invention, a system forautomated construction of inconspicuous seamlines in an orthomosaiccomprising a vector server stored and operating on a network-connectedcomputing device, a raster server stored and operating on anetwork-connected computing device, a mosaic construction engine storedand operating on a network-connected computing device, a featureextraction engine stored and operating on a network-connected computingdevice, a seamline construction engine stored and operating on anetwork-connected computing device, and a rendering engine stored andoperating on a network-connected computing device, is disclosed.According to the embodiment, a raster server may retrieve orthorectifiedraster images from a raster storage, for example, such as satelliteimages or similar raster image data that depict an actual physicalenvironment. Retrieved rasters may be provided to a mosaic constructionengine, which first co-registers and tonally balances the raster images,then sends requests to the seamline construction engine to build theseamlines. Each seamline request involves a pair of overlapping images Aand B. The seamline construction engine calls the feature extractionengine to identify those pixels in image A and image B (within theoverlap region) associated with certain classes of features,particularly linear features. The seamline construction engine builds acost raster from the results of the feature extraction engine, andextracts the seamline as a least cost path from the cost raster. Theseamline construction engine sends requested seamline vectors back tothe mosaic construction engine, which then clips the original rasterimages against the seamlines to form the orthomosaic.

The orthomosaic may then be provided to a rendering engine, as may bepresentable on a viewer such as a display screen, for example for reviewby a human user. Additionally, a user may manipulate the visualizationusing a variety of input devices such as, for example, a computer mouseor keyboard to zoom in or zoom out. As needed, the seamline vectors ofthe mosaic may be sent to the vector server and persisted in the vectorstorage for future reference. The vector storage might be a database orother data storage means (such as, for example, integral or removablehardware-based storage such as a hard disk drive, or software-basedstorage schema common in the art.)

BRIEF DESCRIPTION OF THE DRAWING FIGURES

The accompanying drawings illustrate several embodiments of theinvention and, together with the description, serve to explain theprinciples of the invention according to the embodiments. It will beappreciated by one skilled in the art that the particular embodimentsillustrated in the drawings are merely exemplary, and are not to beconsidered as limiting of the scope of the invention or the claimsherein in any way.

FIG. 1 is a block diagram illustrating an exemplary hardwarearchitecture of a computing device used in an embodiment of theinvention.

FIG. 2 is a block diagram illustrating an exemplary logical architecturefor a client device, according to an embodiment of the invention.

FIG. 3 is a block diagram showing an exemplary architectural arrangementof clients, servers, and external services, according to an embodimentof the invention.

FIG. 4 is another block diagram illustrating an exemplary hardwarearchitecture of a computing device used in various embodiments of theinvention.

FIG. 5 is a block diagram of an exemplary system architecture for theautomated construction of inconspicuous seamlines in an orthomosaic,according to a preferred embodiment of the invention.

FIG. 6 is a flow diagram illustrating an exemplary method for theautomated construction of an inconspicuous seamline within the overlapregion of two images, according to a preferred embodiment of theinvention.

DETAILED DESCRIPTION

The inventor has conceived and reduced to practice, in a preferredembodiment of the invention, a system and method for automatedconstruction of inconspicuous seamlines in an orthomosaic, the seamlinesrealized as least cost paths extracted from respective cost rasters. Thekey aspect of the invention is the design of the cost raster itself,which yields inconspicuous seamlines over a diverse range of imagecontent, especially in the most complex areas where there is humandevelopment.

One or more different inventions may be described in the presentapplication. Further, for one or more of the inventions describedherein, numerous alternative embodiments may be described; it should beappreciated that these are presented for illustrative purposes only andare not limiting of the inventions contained herein or the claimspresented herein in any way. One or more of the inventions may be widelyapplicable to numerous embodiments, as may be readily apparent from thedisclosure. In general, embodiments are described in sufficient detailto enable those skilled in the art to practice one or more of theinventions, and it should be appreciated that other embodiments may beutilized and that structural, logical, software, electrical and otherchanges may be made without departing from the scope of the particularinventions. Accordingly, one skilled in the art will recognize that oneor more of the inventions may be practiced with various modificationsand alterations. Particular features of one or more of the inventionsdescribed herein may be described with reference to one or moreparticular embodiments or figures that form a part of the presentdisclosure, and in which are shown, by way of illustration, specificembodiments of one or more of the inventions. It should be appreciated,however, that such features are not limited to usage in the one or moreparticular embodiments or figures with reference to which they aredescribed. The present disclosure is neither a literal description ofall embodiments of one or more of the inventions nor a listing offeatures of one or more of the inventions that must be present in allembodiments.

Headings of sections provided in this patent application and the titleof this patent application are for convenience only, and are not to betaken as limiting the disclosure in any way.

Devices that are in communication with each other need not be incontinuous communication with each other, unless expressly specifiedotherwise. In addition, devices that are in communication with eachother may communicate directly or indirectly through one or morecommunication means or intermediaries, logical or physical.

A description of an embodiment with several components in communicationwith each other does not imply that all such components are required. Tothe contrary, a variety of optional components may be described toillustrate a wide variety of possible embodiments of one or more of theinventions and in order to more fully illustrate one or more aspects ofthe inventions. Similarly, although process steps, method steps,algorithms or the like may be described in a sequential order, suchprocesses, methods and algorithms may generally be configured to work inalternate orders, unless specifically stated to the contrary. In otherwords, any sequence or order of steps that may be described in thispatent application does not, in and of itself, indicate a requirementthat the steps be performed in that order. The steps of describedprocesses may be performed in any order practical. Further, some stepsmay be performed simultaneously despite being described or implied asoccurring non-simultaneously (e.g., because one step is described afterthe other step). Moreover, the illustration of a process by itsdepiction in a drawing does not imply that the illustrated process isexclusive of other variations and modifications thereto, does not implythat the illustrated process or any of its steps are necessary to one ormore of the invention(s), and does not imply that the illustratedprocess is preferred. Also, steps are generally described once perembodiment, but this does not mean they must occur once, or that theymay only occur once each time a process, method, or algorithm is carriedout or executed. Some steps may be omitted in some embodiments or someoccurrences, or some steps may be executed more than once in a givenembodiment or occurrence.

When a single device or article is described herein, it will be readilyapparent that more than one device or article may be used in place of asingle device or article. Similarly, where more than one device orarticle is described herein, it will be readily apparent that a singledevice or article may be used in place of the more than one device orarticle.

The functionality or the features of a device may be alternativelyembodied by one or more other devices that are not explicitly describedas having such functionality or features. Thus, other embodiments of oneor more of the inventions need not include the device itself.

Techniques and mechanisms described or referenced herein will sometimesbe described in singular form for clarity. However, it should beappreciated that particular embodiments may include multiple iterationsof a technique or multiple instantiations of a mechanism unless notedotherwise. Process descriptions or blocks in figures should beunderstood as representing modules, segments, or portions of code whichinclude one or more executable instructions for implementing specificlogical functions or steps in the process. Alternate implementations areincluded within the scope of embodiments of the present invention inwhich, for example, functions may be executed out of order from thatshown or discussed, including substantially concurrently or in reverseorder, depending on the functionality involved, as would be understoodby those having ordinary skill in the art.

Hardware Architecture

Generally, the techniques disclosed herein may be implemented onhardware or a combination of software and hardware. For example, theymay be implemented in an operating system kernel, in a separate userprocess, in a library package bound into network applications, on aspecially constructed machine, on an application-specific integratedcircuit (ASIC), or on a network interface card.

Software/hardware hybrid implementations of at least some of theembodiments disclosed herein may be implemented on a programmablenetwork-resident machine (which should be understood to includeintermittently connected network-aware machines) selectively activatedor reconfigured by a computer program stored in memory. Such networkdevices may have multiple network interfaces that may be configured ordesigned to utilize different types of network communication protocols.A general architecture for some of these machines may be describedherein in order to illustrate one or more exemplary means by which agiven unit of functionality may be implemented. According to specificembodiments, at least some of the features or functionalities of thevarious embodiments disclosed herein may be implemented on one or moregeneral-purpose computers associated with one or more networks, such asfor example an end-user computer system, a client computer, a networkserver or other server system, a mobile computing device (e.g., tabletcomputing device, mobile phone, smartphone, laptop, or other appropriatecomputing device), a consumer electronic device, a music player, or anyother suitable electronic device, router, switch, or other suitabledevice, or any combination thereof. In at least some embodiments, atleast some of the features or functionalities of the various embodimentsdisclosed herein may be implemented in one or more virtualized computingenvironments (e.g., network computing clouds, virtual machines hosted onone or more physical computing machines, or other appropriate virtualenvironments).

Referring now to FIG. 1, there is shown a block diagram depicting anexemplary computing device 100 suitable for implementing at least aportion of the features or functionalities disclosed herein. Computingdevice 100 may be, for example, any one of the computing machines listedin the previous paragraph, or indeed any other electronic device capableof executing software- or hardware-based instructions according to oneor more programs stored in memory. Computing device 100 may be adaptedto communicate with a plurality of other computing devices, such asclients or servers, over communications networks such as a wide areanetwork a metropolitan area network, a local area network, a wirelessnetwork, the Internet, or any other network, using known protocols forsuch communication, whether wireless or wired.

In one embodiment, computing device 100 includes one or more centralprocessing units (CPU) 102, one or more interfaces 110, and one or morebusses 106 (such as a peripheral component interconnect (PCI) bus). Whenacting under the control of appropriate software or firmware, CPU 102may be responsible for implementing specific functions associated withthe functions of a specifically configured computing device or machine.For example, in at least one embodiment, a computing device 100 may beconfigured or designed to function as a server system utilizing CPU 102,local memory 101 and/or remote memory 120, and interface(s) 110. In atleast one embodiment, CPU 102 may be caused to perform one or more ofthe different types of functions and/or operations under the control ofsoftware modules or components, which for example, may include anoperating system and any appropriate applications software, drivers, andthe like.

CPU 102 may include one or more processors 103 such as, for example, aprocessor from one of the Intel, ARM, Qualcomm, and AMD families ofmicroprocessors. In some embodiments, processors 103 may includespecially designed hardware such as application-specific integratedcircuits (ASICs), electrically erasable programmable read-only memories(EEPROMs), field-programmable gate arrays (FPGAs), and so forth, forcontrolling operations of computing device 100. In a specificembodiment, a local memory 101 (such as non-volatile random accessmemory (RAM) and/or read-only memory (ROM), including for example one ormore levels of cached memory) may also form part of CPU 102. However,there are many different ways in which memory may be coupled to system100. Memory 101 may be used for a variety of purposes such as, forexample, caching and/or storing data, programming instructions, and thelike. It should be further appreciated that CPU 102 may be one of avariety of system-on-a-chip (SOC) type hardware that may includeadditional hardware such as memory or graphics processing chips, such asa Qualcomm SNAPDRAGON™ or Samsung EXYNOS™ CPU as are becomingincreasingly common in the art, such as for use in mobile devices orintegrated devices.

As used herein, the term “processor” is not limited merely to thoseintegrated circuits referred to in the art as a processor, a mobileprocessor, or a microprocessor, but broadly refers to a microcontroller,a microcomputer, a programmable logic controller, anapplication-specific integrated circuit, and any other programmablecircuit.

In one embodiment, interfaces 110 are provided as network interfacecards (NICs). Generally, NICs control the sending and receiving of datapackets over a computer network; other types of interfaces 110 may forexample support other peripherals used with computing device 100. Amongthe interfaces that may be provided are Ethernet interfaces, frame relayinterfaces, cable interfaces, DSL interfaces, token ring interfaces,graphics interfaces, and the like. In addition, various types ofinterfaces may be provided such as, for example, universal serial bus(USB), Serial, Ethernet, FIREWIRE™, THUNDERBOLT™, PCI, parallel, radiofrequency (RF), BLUETOOTH™, near-field communications (e.g., usingnear-field magnetics), 802.11 (WiFi), frame relay, TCP/IP, ISDN, fastEthernet interfaces, Gigabit Ethernet interfaces, Serial ATA (SATA) orexternal SATA (ESATA) interfaces, high-definition multimedia interface(HDMI), digital visual interface (DVI), analog or digital audiointerfaces, asynchronous transfer mode (ATM) interfaces, high-speedserial interface (HSSI) interfaces, Point of Sale (POS) interfaces,fiber data distributed interfaces (FDDIs), and the like. Generally, suchinterfaces 110 may include physical ports appropriate for communicationwith appropriate media. In some cases, they may also include anindependent processor (such as a dedicated audio or video processor, asis common in the art for high-fidelity AN hardware interfaces) and, insome instances, volatile and/or non-volatile memory (e.g., RAM).

Although the system shown in FIG. 1 illustrates one specificarchitecture for a computing device 100 for implementing one or more ofthe inventions described herein, it is by no means the only devicearchitecture on which at least a portion of the features and techniquesdescribed herein may be implemented. For example, architectures havingone or any number of processors 103 may be used, and such processors 103may be present in a single device or distributed among any number ofdevices. In one embodiment, a single processor 103 handlescommunications as well as routing computations, while in otherembodiments a separate dedicated communications processor may beprovided. In various embodiments, different types of features orfunctionalities may be implemented in a system according to theinvention that includes a client device (such as a tablet device orsmartphone running client software) and server systems (such as a serversystem described in more detail below).

Regardless of network device configuration, the system of the presentinvention may employ one or more memories or memory modules (such as,for example, remote memory block 120 and local memory 101) configured tostore data, program instructions for the general-purpose networkoperations, or other information relating to the functionality of theembodiments described herein (or any combinations of the above). Programinstructions may control execution of or comprise an operating systemand/or one or more applications, for example. Memory 120 or memories101, 120 may also be configured to store data structures, configurationdata, encryption data, historical system operations information, or anyother specific or generic non-program information described herein.

Because such information and program instructions may be employed toimplement one or more systems or methods described herein, at least somenetwork device embodiments may include nontransitory machine-readablestorage media, which, for example, may be configured or designed tostore program instructions, state information, and the like forperforming various operations described herein. Examples of suchnontransitory machine-readable storage media include, but are notlimited to, magnetic media such as hard disks, floppy disks, andmagnetic tape; optical media such as CD-ROM disks; magneto-optical mediasuch as optical disks, and hardware devices that are speciallyconfigured to store and perform program instructions, such as read-onlymemory devices (ROM), flash memory (as is common in mobile devices andintegrated systems), solid state drives (SSD) and “hybrid SSD” storagedrives that may combine physical components of solid state and hard diskdrives in a single hardware device (as are becoming increasingly commonin the art with regard to personal computers), memristor memory, randomaccess memory (RAM), and the like. It should be appreciated that suchstorage means may be integral and non-removable (such as RAM hardwaremodules that may be soldered onto a motherboard or otherwise integratedinto an electronic device), or they may be removable such as swappableflash memory modules (such as “thumb drives” or other removable mediadesigned for rapidly exchanging physical storage devices),“hot-swappable” hard disk drives or solid state drives, removableoptical storage discs, or other such removable media, and that suchintegral and removable storage media may be utilized interchangeably.Examples of program instructions include both object code, such as maybe produced by a compiler, machine code, such as may be produced by anassembler or a linker, byte code, such as may be generated by forexample a Java™ compiler and may be executed using a Java virtualmachine or equivalent, or files containing higher level code that may beexecuted by the computer using an interpreter (for example, scriptswritten in Python, Perl, Ruby, Groovy, or any other scripting language).

In some embodiments, systems according to the present invention may beimplemented on a standalone computing system. Referring now to FIG. 2,there is shown a block diagram depicting a typical exemplaryarchitecture of one or more embodiments or components thereof on astandalone computing system. Computing device 200 includes processors210 that may run software that carry out one or more functions orapplications of embodiments of the invention, such as for example aclient application 230. Processors 210 may carry out computinginstructions under control of an operating system 220 such as, forexample, a version of Microsoft's WINDOWS™ operating system, Apple's MacOS/X or iOS operating systems, some variety of the Linux operatingsystem, Google's ANDROID™ operating system, or the like. In many cases,one or more shared services 225 may be operable in system 200, and maybe useful for providing common services to client applications 230.Services 225 may for example be WINDOWS™ services, user-space commonservices in a Linux environment, or any other type of common servicearchitecture used with operating system 210. Input devices 270 may be ofany type suitable for receiving user input, including for example akeyboard, touchscreen, microphone (for example, for voice input), mouse,touchpad, trackball, or any combination thereof. Output devices 260 maybe of any type suitable for providing output to one or more users,whether remote or local to system 200, and may include for example oneor more screens for visual output, speakers, printers, or anycombination thereof. Memory 240 may be random-access memory having anystructure and architecture known in the art, for use by processors 210,for example to run software. Storage devices 250 may be any magnetic,optical, mechanical, memristor, or electrical storage device for storageof data in digital form (such as those described above, referring toFIG. 1). Examples of storage devices 250 include flash memory, magnetichard drive, CD-ROM, and/or the like.

In some embodiments, systems of the present invention may be implementedon a distributed computing network, such as one having any number ofclients and/or servers. Referring now to FIG. 3, there is shown a blockdiagram depicting an exemplary architecture 300 for implementing atleast a portion of a system according to an embodiment of the inventionon a distributed computing network. According to the embodiment, anynumber of clients 330 may be provided. Each client 330 may run softwarefor implementing client-side portions of the present invention; clientsmay comprise a system 200 such as that illustrated in FIG. 2. Inaddition, any number of servers 320 may be provided for handlingrequests received from one or more clients 330. Clients 330 and servers320 may communicate with one another via one or more electronic networks310, which may be in various embodiments any of the Internet, a widearea network, a mobile telephony network (such as CDMA or GSM cellularnetworks), a wireless network (such as WiFi, WiMAX, LTE, and so forth),or a local area network (or indeed any network topology known in theart; the invention does not prefer any one network topology over anyother). Networks 310 may be implemented using any known networkprotocols, including for example wired and/or wireless protocols.

In addition, in some embodiments, servers 320 may call external services370 when needed to obtain additional information, or to refer toadditional data concerning a particular call. Communications withexternal services 370 may take place, for example, via one or morenetworks 310. In various embodiments, external services 370 may compriseweb-enabled services or functionality related to or installed on thehardware device itself. For example, in an embodiment where clientapplications 230 are implemented on a smartphone or other electronicdevice, client applications 230 may obtain information stored in aserver system 320 in the cloud or on an external service 370 deployed onone or more of a particular enterprise's or user's premises.

In some embodiments of the invention, clients 330 or servers 320 (orboth) may make use of one or more specialized services or appliancesthat may be deployed locally or remotely across one or more networks310. For example, one or more databases 340 may be used or referred toby one or more embodiments of the invention. It should be understood byone having ordinary skill in the art that databases 340 may be arrangedin a wide variety of architectures and using a wide variety of dataaccess and manipulation means. For example, in various embodiments oneor more databases 340 may comprise a relational database system using astructured query language (SQL), while others may comprise analternative data storage technology such as those referred to in the artas “NoSQL” (for example, Hadoop CASSANDRA™, Google BIGTABLE™, and soforth). In some embodiments, variant database architectures such ascolumn-oriented databases, in-memory databases, clustered databases,distributed databases, or even flat file data repositories may be usedaccording to the invention. It will be appreciated by one havingordinary skill in the art that any combination of known or futuredatabase technologies may be used as appropriate, unless a specificdatabase technology or a specific arrangement of components is specifiedfor a particular embodiment herein. Moreover, it should be appreciatedthat the term “database” as used herein may refer to a physical databasemachine, a cluster of machines acting as a single database system, or alogical database within an overall database management system. Unless aspecific meaning is specified for a given use of the term “database”, itshould be construed to mean any of these senses of the word, all ofwhich are understood as a plain meaning of the term “database” by thosehaving ordinary skill in the art.

Similarly, most embodiments of the invention may make use of one or moresecurity systems 360 and configuration systems 350. Security andconfiguration management are common information technology (IT) and webfunctions, and some amount of each are generally associated with any ITor web systems. It should be understood by one having ordinary skill inthe art that any configuration or security subsystems known in the artnow or in the future may be used in conjunction with embodiments of theinvention without limitation, unless a specific security 360 orconfiguration system 350 or approach is specifically required by thedescription of any specific embodiment.

FIG. 4 shows an exemplary overview of a computer system 400 as may beused in any of the various locations throughout the system. It isexemplary of any computer that may execute code to process data. Variousmodifications and changes may be made to computer system 400 withoutdeparting from the broader scope of the system and method disclosedherein. CPU 401 is connected to bus 402, to which bus is also connectedmemory 403, nonvolatile memory 404, display 407, I/O unit 408, andnetwork interface card (NIC) 413. I/O unit 408 may, typically, beconnected to keyboard 409, pointing device 410, hard disk 412, andreal-time clock 411. NIC 413 connects to network 414, which may be theInternet or a local network, which local network may or may not haveconnections to the Internet. Also shown as part of system 400 is powersupply unit 405 connected, in this example, to ac supply 406. Not shownare batteries that could be present, and many other devices andmodifications that are well known but are not applicable to the specificnovel functions of the current system and method disclosed herein. Itshould be appreciated that some or all components illustrated may becombined, such as in various integrated applications (for example,Qualcomm or Samsung SOC-based devices), or whenever it may beappropriate to combine multiple capabilities or functions into a singlehardware device (for instance, in mobile devices such as smartphones,video game consoles, in-vehicle computer systems such as navigation ormultimedia systems in automobiles, or other integrated hardwaredevices).

In various embodiments, functionality for implementing systems ormethods of the present invention may be distributed among any number ofclient and/or server components. For example, various software modulesmay be implemented for performing various functions in connection withthe present invention, and such modules may be variously implemented torun on server and/or client components.

Conceptual Architecture

FIG. 5 is a block diagram of an exemplary system architecture 500 forsemi-automated feature extraction, according to a preferred embodimentof the invention. According to the embodiment, an image analysis server501 that may be a computing device comprising program code stored in amemory and adapted to perform analysis operations on received vectorssuch as (for example) retrieving and analyzing vectors from a database502 that may be a computing device comprising program code stored in amemory and adapted to store and provide data to other components of asystem 500. These analyzed images may then be provided to a cutlineextraction server 503 that may be a computing device comprising programcode stored in a memory and adapted to process images to identifyfeatures based at least in part on image content, that may then identifyimage features such as (for example) roads or other linear features, andcompute a cost raster based at least in part on features identified in agiven image, for example to identify roads in a satellite photograph anddetermine a cost raster to identify possible routes and paths based onthe roads or terrain identified in the image.

Calculated image information or cost rasters may then be provided to arendering engine 504, that may analyze the routes and formvisualizations of the combined vector and raster data such as may bepresentable on a viewer 506 such as a display screen, for example forreview by a human user. Additionally, a user may interact with thevisualization presented using a variety of input devices 505 such as(for example) a computer mouse or keyboard, such as to manipulate thevisualization or modify the information being presented. User input maybe received by the rendering engine 504 and utilized to update therendering appropriately (such as to zoom in or out, for example), or maybe further provided by the rendering engine 504 to a feature extractionserver 503 as needed, for example to specify new features based on usermodification, or to correct an erroneous or imprecise feature.

Additionally, a mosaic imaging server 510 may be utilized to receive andprocess images or image tiles (that may portions or edited versions ofimages, for example cropping a single large image into multiple smallerimage tiles for ease of use), and may provide these image tiles andmosaics to the image analysis server 501 and feature extraction server503 for use in vector operations. For example, a plurality of images maybe processed by the mosaic imaging server 510 for use as raster imagecomponents to be presented optionally with vector information, such asfor display and interaction via a viewer 506. The mosaic imaging server510 may perform such processing operations as to determine bias oroffset values for image tiles, to align and match such tiles to formimage mosaics (that is, a single composite image from multiple smallerimages or tiles), as well as to provide image-based information for usein editing, calculation, or extraction operations according to theembodiment of the invention.

It should be appreciated that according to the embodiment, various meansof connection or communication between the components of a system 500may be utilized according to the invention interchangeably orsimultaneously, such as for example a direct, physical data connection(such as via a data cable or similar physical means), a software-basedconnection such as via an application programming interface (API) orother software communication means (such as may be suitable, forexample, in arrangements where multiple system components may operate ona single hardware device such as a computing server or workstation), orany of a variety of network connections such as via the Internet orother data communications network. It should therefore be appreciatedthat the connections shown are exemplary in nature and represent only aselection of possible arrangements, and that alternate or additionalconnections may be utilized according to the invention.

DETAILED DESCRIPTION OF EXEMPLARY EMBODIMENTS

FIG. 6 is a flow diagram illustrating an exemplary method 600 for theautomated construction of an inconspicuous seamline from point P topoint Q within the overlap region of images A and B, according to apreferred embodiment of the invention. The points P and Q are where thetwo image boundaries intersect.

In an initial step 601, the seamline construction server may receive asinput a pair of tonally balanced, high-resolution, orthorectified,co-registered (to within a few meters on flat land), pixel-alignedimages A and B. It is assumed for the present embodiment that each imagehas a multi-spectral blue-green (BGRN) representative and a panchromatic(PAN) representative. It is further assumed for the embodiment that thenative PAN resolution from the sensor is at most 1 m and the native BGRNresolution from the sensor is at most 4 m. It is further assumed for theembodiment that all image representatives have been resampled to acommon pixel size between 0.75 m and 1 m. It is further assumed for theembodiment that the BGRN images have been atmospherically corrected, andthat the PAN images have either been atmospherically corrected or insome other way grayscale-normalized (i.e., subjected to a dynamic rangeadjustment algorithm.)

In a next step 602, the seamline construction server may process the PANimages to remove small particles and very thin linear features fromthese images. This processing is designed to remove vehicles and stripesfrom the roads, making roads look more uniform. In a next step 603, theseamline construction server (working with the feature extractionserver) may compute a plurality of derived images from the PAN and BGRNimages related to particular linear features (such as roads, trails,single-line drainages, farm field boundaries, city boundaries, forestboundaries, mountain crests and ravines, and other boundaries thatindicate sharp changes in brightness, hue, or colorfulness) and otherfeatures (such as shadow, cloud, snow, water bodies, rivers, vegetation,and forest). The derived images manifest pixels on these features. Thederived images are computed by applying various filters (e.g., texture,edge, brightness, hue, colorfulness, NDVI, and various morphologicaloperators for solidifying, cleaning, removing holes and nicks, etc.)

In a next step 604, the seamline construction server may compute a costraster based on the derived images. Linear feature pixels that arecommon to both images (e.g. both images A and B may agree that the samelocation is a road pixel) will generally be assigned low cost—these aredesirable pixels for a seamline to pass through. Seamlines are ofteninconspicuous on common linear features because linear features, beingeither narrow channels (e.g., road, trail) or boundaries (e.g., edge offorest, edge of farm field), are places where transitions in imagecontent are occurring anyway and are thus effective at hiding aseamlines. In a next step 605, the seamline construction server maycompute the seamline as a least cost pixel path from point P to point Qwithin the cost raster. This pixel path is then vectorized and sent tothe mosaic construction server.

The various processes or algorithms mentioned in the steps of the method600 are explained further below, and it should be appreciated that whilereference may be made to specific types of image information or details,these are all provided as exemplary and it should be appreciated that avariety of additional or alternate image details or features may beutilized or derived according to the embodiment.

A seamline request is associated with a pair of images A and B thatoverlap, and two specified terminal points P and Q The points P and Qmay be at the locations where the boundaries of image A and B intersect.In the present embodiment, the images A and B are assumed to be tonallybalanced (to each other), high-resolution, orthorectified, co-registered(to within a few meters on flat land), and pixel-aligned. It is assumedfor the present embodiment that each image has a multi-spectral BGRNrepresentative and a PAN representative. It is further assumed for theembodiment that the native PAN resolution from the sensor is at most 1 mand the native BGRN resolution from the sensor is at most 4 m. It isfurther assumed for the embodiment that all image representatives havebeen resampled to a common pixel size between 0.75 m and 1 m. It isfurther assumed for the embodiment that the BGRN images have beenatmospherically corrected, and that the PAN images have either beenatmospherically corrected or in some other way grayscale-normalized(i.e., subjected to a dynamic range adjustment algorithm.)

For narrow linear channels such as roads, a pixel may be said to lie ona “common road” if it lies on road in both image A and image B. Forboundaries such as forest boundary, a pixel may be said to lie on“common forest boundary” if it lies near forest boundary in both image Aand image B. For broad areas such as forest, a pixel may be said to lieon “common forest” if it lies on forest in image A and image B.

In a preferred embodiment, the cost raster assigns low cost to pixels ofthe following types (giving the seamline ample opportunity to find aninconspicuous trajectory):

-   -   Common road, trail, and single-line drainage    -   Common farm field boundary    -   Common forest boundary    -   Common mountain crests and ravines    -   Common shore around water bodies    -   Common boundary where there is an abrupt change in brightness,        colorfulness, hue, or texture    -   Common shadow areas    -   Common forest areas of similar color tonality    -   Common low-texture areas of very similar color tonality    -   Boundary of the union of city region in A and city region in B    -   Narrow bands of vegetation in either image

In a preferred embodiment, the cost raster assigns high cost to pixelsof the following types (which often do not lend themselves well to aninconspicuous seamline):

-   -   Water areas in either image    -   Snow areas in either image    -   Cloud in either image    -   Cloud shadow in either image    -   Very bright areas in either image    -   Non-forest high-texture areas in either image    -   Low-texture areas of dissimilar tonality    -   Black fill in either image    -   Exclusive-OR of shadow areas    -   Exclusive-OR of vegetation areas

In a preferred embodiment, a baseline middle cost (between low and high)is assigned to all other pixels (not covered by the previous twoparagraphs) in the cost raster.

In a preferred embodiment, the cost raster is built from a sequentialprecedence ordering (lowest precedence to highest precedence) of thepixel types characterized above. If a pixel is of more than one type,then of those types, the one of highest precedence determines which cost(low, medium, high) is assigned to the pixel in the cost raster. This ishow ties are broken in deciding which cost to assign any given pixel inthe cost raster.

It remains to describe, for an embodiment, how the pixels of each typeare automatically and sufficiently identified in the images A and B. Toremove traffic from the roads, segmentation of the PAN may be used tofind small bright particles, with each such particle replaced by themedian pixel value on its outer boundary. To remove stripes from theroads, a kind of median filter may be applied to the PAN. Road, trail,and single-line drainage pixels may be identified in the PAN.High-texture pixels may be identified from the PAN as pixels at thecenters of local regions showing large variability in their grayscalevalues. Vegetation pixels may be identified from the BGRN as those withhigh NDVI. Forest pixels may be identified as vegetation pixels withhigh-texture. Farm field boundary may be identified as hard edge pixels(from PAN) against low-texture (from PAN) vegetation (from BGRN).Mountain crests and ravines may be identified in the PAN by degradingthe PAN using aggregation, and identifying hard edge pixels in thedegraded image. Water body pixels may be identified in the PAN as verydark pixels, or in the BGRN as very blue pixels or a water index. Shadowpixels may be identified from the PAN as very dark pixels. City pixelsmay be identified as a morphological closure of hard edge pixels (fromPAN) that originates shadow (from PAN and sun azimuth). Pixels ofsimilar color tonality between BGRN A and BGRN B may be determined byfirst applying small-scale smoothing to each image and then computing ameasure of spectral distance between corresponding pixels in the twoimages. Cloud and snow pixels may be identified as very bright pixels(from PAN) that form large cohesive connected components. Cloud shadowpixels may be identified as very dark pixels (from PAN) that form largecohesive connected components.

In describing the steps above, which participate in the construction ofthe cost raster, it should be appreciated that mention of numerousmorphological processing steps (dilation, erosion, opening, closure,filling of small holes, etc.) were omitted for brevity, as they were notnecessary to mention for one to understand the overall method.

The skilled person will be aware of a range of possible modifications ofthe various embodiments described above. Accordingly, the presentinvention is defined by the claims and their equivalents.

What is claimed is:
 1. A method for creating seamlines in orthomosaicimagery using a cost, comprising the steps of: receiving, at an imageanalysis server, a plurality of input images; identifying, using afeature extraction server, a plurality of linear image features withinthe plurality of input images; computing a cost raster based at least inpart on at least a portion of the plurality of image featuresidentified; automatically generating seamlines along at least some ofthe linear image features using cost minimization; and vectorizing thegenerated seamlines.